The majority of tumors carry somatic mutations in one or more known oncogenes and tumor suppressor genes. Because mutation can occur anywhere in the gene, and because the specific location and identity of a given mutation within the gene may significantly influence tumor aggressiveness and response to treatment, it is important to scan the entire gene for mutation, not just a few sites. It is also important to be able to detect mutant alleles that are in the minority in the sample because tumors frequently contain a mixture of malignant and non-malignant cells, with the nonmalignant cells often outnumbering the malignant. Existing technologies, however, are limited either in their ability to detect minority variants or in their ability to scan the entire sequence for mutation. SpectraGenetics' Peptide Mass Signature Genotyping (PMSG) technology has neither of these limitations, giving it the potential to meet the need for sensitive and accurate analysis of oncogene and tumor suppressor genes. As currently practiced, PMSG analyzes genomic DNA. In the project proposed here, the PMSG process will be adapted to the analysis of mRNA. The new process, RT-PMSG, will generate cDNAs that will be used to produce recombinant polypeptides for mutation analysis by MALDI-TOF mass spectrometry. This approach should be particularly sensitive for cases where the gene of interest is overexpressed in the malignant cells. The RT-PMSG process is expected to provide quality genotyping data into a market requiring a low-cost and reliable method for identifying and characterizing oncogene and tumor suppressor mutations in nucleic acid samples taken directly from tumors. The initial experiments will analyze the TP53 gene, a gene that is mutated and/or overexpressed in most human cancers. This proposal describes specific proof-of-concept experiments to develop reliable protocols for RT-PCR, protein expression and purification, and MALDI-TOF analysis of recombinant p53. Protocols for cleavage of the protein into reproducible sets of peptides accounting for the entire p53 protein sequence will be developed to provide enhanced sensitivity and accuracy. Consistent detection of mutations will be demonstrated using 9 cell lines and using mixing experiments to simulate tumors and validate the prototype concept. Phase II development will include expression in multiple reading frames, software development to increase accuracy and comprehensiveness, and automation to improve reproducibility and reduce cost resulting in a technically superior genotyping product for research and biopharmaceutical markets.